Abstract
The key step of bearing fault diagnosis is to select a suitable resonance frequency band, so as to filter out interference components to the maximum extent and retain fault information in the resonance band. Kurtogram algorithm can locate the resonance frequency band well, which has been widely researched and applied in recent years, and has produced many derivative algorithms. The statistical indicators used by these methods to identify frequency band features are divided into time domain indicators and frequency domain indicators. Time domain indicators are more sensitive to a single accidental impact components, while frequency domain indicators are easily affected by harmonics in the time domain, that is, single or several frequency extremes in the frequency domain. In order to overcome the impact of non-periodic transient impulse components and modulation harmonic components, this article proposes a new method. This method uses wavelet packet transform (WPT) to divide the frequency band plane, and adopts 3 iterations 1.5-dimensional spectrum (1.5D spectrum) method, which can eliminate the impulse interference that has no coupling relationship in the time domain and frequency domain. Based on the above process, the $\text{K}_{\mathrm {I-1.5D}}$ gram method is constructed, which can realize more accurate positioning of the fault information. Finally, through simulated and experimental analysis, the effectiveness of the proposed method is verified.
Highlights
As the joint of rotating machinery, rolling bearing is one of the most widely used parts in rotating machinery, with high failure rate and large life span
The results show that neither the Ksegram algorithm defined in time domain nor the Ksesgram algorithm defined in frequency domain can accurately locate the sub-band of periodic impulse components
The results show that the non-periodic transient impulse components and harmonic components that do not have a coupling relationship in the time and frequency domains have been eliminated, and only the periodic impulse components with the coupling relationship have been retained
Summary
As the joint of rotating machinery, rolling bearing is one of the most widely used parts in rotating machinery, with high failure rate and large life span. When dealing with extreme signals, such as when the processing signal contains non-periodic transient impulse components and modulation harmonic components, the processing capability of the algorithm faces challenges Aiming at this problem, this article proposes an iterative 1.5-dimensional spectral kurtosis method, which can suppress the components that do not have a coupling relationship in the signal and avoid the influence of these components on the statistical feature indicators, thereby improving the accuracy of frequency band selection. ITERATIVE 1.5D SPECTRAL KURTOSIS ALGORITHM In order to solve the non-periodic transient impulse interference in the time domain and the harmonic singular line interference in the frequency domain at the same time, an iterative 1.5D spectral kurtosis processing method is proposed
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call